In today's world, people and businesses retain extensive amounts of data in various databases. In addition, it is rather common nowadays for a user to be registered with a large number of software applications, by providing different user's details (such as an e-address and perhaps other associated details) in the registration process with each of these software applications. Thus, users often have different user names in various applications (which may also be defined in different formats), and receive and send messages over a variety of wired and wireless networks via a variety of devices, such as desktop computers, wired phones, wireless devices (e.g., phones and personal digital assistants (“PDAs”)), and others, where certain details associated with the users' contact details are stored.
Moreover, it often happens that when a user wants to communicate with another user, not only that the details of that other user must be retrieved from a different database (e.g. depending on the medium that the user selects for establishing such a communication session), also the required information may be stored in a language different from the one currently used by that user.
Therefore, there is a need to be able to generate a consolidated text record that preferably includes all retrievable contact details for a single entry from various databases, irrespective of the language in which they were entered. However, there are several problems which limit the ability to find all the relevant data associated with an entity in various databases. Multiple data records may exist for a particular entity as a result of separate data records received from one or more information sources, which in turn leads to a problem that may be referred to as data fragmentation. In case of data fragmentation, a query of the master database may not retrieve all of the relevant information about a particular entity. In addition, as described above, the query may miss some relevant information about an entity due to a typographical error made during the entry of the data, which would lead to the problem of data inaccessibility. These problems limit the ability to locate the information for a particular entity within one or more databases.
In order to reduce the amount of data that must be reviewed, and prevent the user from picking the wrong data record, it is also desirable to identify and associate data records from various information sources that may contain information about the same entity. There are conventional systems that locate duplicate data records within a database and delete those duplicate data records, but these systems may only locate data records which are essentially identical to each other. Thus, these conventional systems cannot determine if two data records for example, entered in two different languages, contain nevertheless information about the same entity. In addition, these conventional systems do not attempt to index data records from a plurality of different information sources, and do not locate data records within the one or more information sources containing information about the same entity, to enable linking those data records together. Consequently, it would be desirable to be able to associate data records from a plurality of information sources which pertain to the same entity, despite discrepancies between attributes of these data records and to be able to assemble and present information from these various data records in a cohesive manner. However, in practice it might be extremely difficult to provide an accurate, consolidated view of information from a plurality of information sources. This is true when all the information is retrieved from sources handled in one language. The challenge is naturally even greater in cases where data records are stored in more than one language, in a number of information sources.
There are translation programs that may conduct a search for a word in the non-native language entered by the user and find its explanation in the native language. However, if the word is not presented in a written form to the user, he cannot know exactly how to spell the word. In such a case, the user cannot use usual translation software for translation. In order to overcome this problem, some solutions are described in the art which propose to employ a speech input method for the translation. Such a method uses a speech-to-text conversion engine for converting the speech into text, and then translates the converted text as if it were input text in any of the known methods for translating a text. However, the problem with such solutions is that not everyone has the same pronunciation for the same word. Thus, the converted word may not be the exact one.
US 20110022378 describes a translation method using phonetic symbol input that includes the steps of: establishing translation words in a translation database, each of the translation words having a corresponding translational explanation; entering an input message that includes at least one phonetic symbol; according to some comparison rule, comparing the input message with the translational explanation corresponding to each of the translation words and, when there is a match, loading the matched translation word from the translation database.
Still, there is a need for a solution that provides means to enable consolidating data retrieved in different languages which pertain to a single user, into one single consolidated database entry.